lpsolve

问题 I have this optimization problem where I am trying to maximize column z based on a unique value from column X, but also within a constraint that each of the unique values picked of X added up column of Y most be less than (in this example) 23. For example, I have this sample data: d=data.frame(x=c(1,1,1,2,2,2,3,3,3),y=c(9,7,5,9,7,5,9,7,5),z=c(25,20,5,20,10,5,10,5,3)) Which looks like this: X Y Z 1 1 9 25 2 1 7 20 3 1 5 5 4 2 9 20 5 2 7 10 6 2 5 5 7 3 9 10 8 3 7 5 9 3 5 5 The result should

问题 lpsolve can be called from a c++ program with main() but I am unable to use it in handlemesage() or any other user-defined method in omnet++ simulation. Any help in this regard is appreciated. Thanks 回答1: Go to project properties --> omnet++ --> select SRC --> Options --> link --> Additional libraries to link with: ( -l option) and insert lpsolve55 and ok Screenshot of the step1 Screenshot of the step2 来源： https://stackoverflow.com/questions/43424829/how-to-use-lpsolve-in-omnet-simple-modules

问题 library(lpSolveAPI) lprec1 <- make.lp(0,nrow(df) add.constraint(lprec1, c(1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0), "<=", as.numeric(ads1)) add.constraint(lprec1, c(0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0), "<=", as.numeric(ads2)) add.constraint(lprec1, c(0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0), "<=", as.numeric(ads3)) add.constraint(lprec1, c(0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0), "<="

问题 library(lpSolveAPI) lprec1 <- make.lp(0,nrow(df) add.constraint(lprec1, c(1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0), "<=", as.numeric(ads1)) add.constraint(lprec1, c(0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0), "<=", as.numeric(ads2)) add.constraint(lprec1, c(0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0), "<=", as.numeric(ads3)) add.constraint(lprec1, c(0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0), "<="

问题 I'm trying to formulate that the variables x,y,z must all be different and that they accept only the values 1, 2 or 3 (this is, of course, a toy example): min: x+y+z; 1 <= x <= 3; 1 <= y <= 3; 1 <= z <= 3; but to make this work I still need either access to boolean operators or to a != operator, which don't seem to exist in lpsolve! How can I go about this? I wanted to do this: x != y; x != z; y != z; Thanks EDIT: Here's my current code: /* Objective function */ min: 1; /* Variable bounds */

问题 I`m trying install lp_solve_5.5.0.15_source.tar.gz & lp_solve_5.5.0.15_Python_source.tar.gz in pyhton27 using windows. I keep facing problems, as below: problem of (vcvarsall.bat) - install MinGw (resolved) proiblem of (-mno-cygwin) - delete (-mno-cygwin) in file:cygwinccompiler.py (resolved) In CMD, using "setup.py install build --compiler=mingw32" as command to install. Till now, I found a strange problem which I cant found any documentation to resolve it. after run the CMD command, It

问题 I am using 'lpSolveAPI' to solve multiple binary linear programming problems in R. How do I get it too return ALL the variable combinations for a maximizing problem. Ive searched the documentation and can not find a command for this. Trying to switch from package 'lpSolve' as it inconsistently crashes R. Here's an example problem: library(lpSolveAPI) #matrix of constraints A <- matrix(rbind( c(1,1,0,0,0,0,0,0), c(1,0,0,0,1,0,0,0), c(0,0,1,0,0,1,0,0), c(0,0,1,0,0,0,1,0), c(0,0,1,0,0,0,0,1), c

问题 How can we solve a linear program using R? I want to solve the following example: min -a -2b +4c Constraints a + b + s1 = 5 a + 3c -s2 = 10 2b - 3c = 20 a >= 0, b >= 0, c >= 0, s1 >= 0, s2 >= 0 The equations might not make total sense. I just need to know the syntax of writing these equations in R. I might write something like this for the above equations require(lpSolve) R.obj <- c(-1,-2,4) R.con <- matrix(c(1,1,1,1,3,-1,2,-3),nrow=3,byrow=TRUE) R.dir <- c("=","=","=") R.rhs <- c(5,10,20) lp

问题 I am new to R and have a particular fantasy sports team optimization problem I would like to solve. I have seen other posts use lpSolve for similar problems but I can not seem to wrap my head around the code. Example data table below. Every player is on a team, plays a particular role, has a salary, and has avg points produced per game. The constraints that I need are I need exactly 8 players. No more than 3 players may come from any one team. There must be at least one player for each role

问题 Can someone help me how to use lpsolve55j.jar on Android device. I tried importing it like every other library (putting it in libs folder and adding it in JavaBuildPath -> Libraries) but I got this error: 03-07 15:28:52.910: W/dalvikvm(3421): Exception Ljava/lang/UnsatisfiedLinkError; thrown while initializing Llpsolve/LpSolve; 03-07 15:28:52.910: D/AndroidRuntime(3421): Shutting down VM 03-07 15:28:52.910: W/dalvikvm(3421): threadid=1: thread exiting with uncaught exception (group=0x9e495930